OBLIMAP parallelization and optimization toward high resolution climate model - ice sheet model coupler

2021 ◽  
Author(s):  
Erwan Raffin ◽  
David Guibert ◽  
Thomas Reerink
Keyword(s):  
High Resolution ◽  
Shared Memory ◽  
Large Scale ◽  
Climate Model ◽  
Climate Modeling ◽  
Parallel Implementation ◽  
Ice Sheet ◽  
Adaptive Mesh ◽  
Test Case ◽  
Single Node

<p>Within the ESiWACE2 project we parallelized and optimized OBLIMAP. OBLIMAP is a climate model - ice sheet model coupler that can be used for offline and online coupling with embeddable mapping routines. In order to anticipate future demand concerning higher resolution and/or adaptive mesh applications, a parallel implementation of OBLIMAP's fortran code with MPI has been developed. The data intense nature of this mapping task, required a shared memory approach across the processors per compute node in order to prevent that the node memory is the limiting bottleneck. Besides, the current parallel implementation allows multi node scaling and includes parallel netcdf IO in addition with loop optimizations. Results show that the new parallel implementation offers better performance and scales well. On a single node, the shared memory approach allows now to use all the available cores, up to 128 cores in our experiments on Antarctica 20x20km test case where the original code was limited to 64 cores on this high-end node and it was even limited to 8 cores on moderate platforms. The multi node parallelization offers on Greenland 2x2km test case a speedup of 4.4x on 4 high-end compute nodes equipped with 128 cores each compared to the original code which was able to run only on 1 node. This paves the way to the establishment of OBLIMAP as an candidate ice sheet coupling library candidate for large-scale, high-resolution climate modeling.</p>

scholarly journals Climate of the Greenland ice sheet using a high-resolution climate model – Part 2: Near-surface climate and energy balance

2010 ◽  
Vol 4 (2) ◽  
pp. 603-639 ◽  
Author(s):  
J. Ettema ◽  
M. R. van den Broeke ◽  
E. van Meijgaard ◽  
W. J. van de Berg
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Katabatic Wind ◽  
Surface Cooling ◽  
Near Surface ◽  
Surface Climate

Abstract. The near-surface climate of the Greenland ice sheet is characterized by persistent katabatic winds and quasi-permanent temperature deficit. Using a high resolution (11 km) regional climate model allows for detailed study of the spatial variability in these phenomena and the underlying atmospheric processes. The near-surface temperature distribution over the ice sheet is clearly affected by elevation, latitude, large scale advection, meso-scale topographic features and the occurrence of summer melt. The lowest annual temperatures of −30.5 °C are found north of the highest elevations of the GrIS, whereas the lowest southern margins are warmest (−3.5 °C). Over the ice sheet, a persistent katabatic wind system develops due to radiative surface cooling and the gently slope of the surface. The strongest wind speeds are seen in the northeast where the strong large scale winds, low cloud cover and concave surface force a continuous supply of cold air, which enhances the katabatic forcing. The radiative cooling of the surface is controlled by the net longwave emission and transport of heat towards the surface by turbulence. In summer this mechanism is much weaker, leading to less horizontal variability in near-surface temperatures and wind speed.

scholarly journals Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

2017 ◽  
Vol 10 (3) ◽  
pp. 1383-1402 ◽  
Author(s):  
Paolo Davini ◽  
Jost von Hardenberg ◽  
Susanna Corti ◽  
Hannah M. Christensen ◽  
Stephan Juricke ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Rainfall Variability ◽  
Global Climate Model ◽  
Small Scale ◽  
Low Resolution ◽  
The Impact ◽  
Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

scholarly journals Modelling the response of the Lambert Glacier–Amery Ice Shelf system, East Antarctica, to uncertain climate forcing over the 21st and 22nd centuries

2014 ◽  
Vol 8 (3) ◽  
pp. 1057-1068 ◽  
Author(s):  
Y. Gong ◽  
S. L. Cornford ◽  
A. J. Payne
Keyword(s):  
Climate Model ◽  
Global Environmental Change ◽  
Ice Sheet ◽  
Adaptive Mesh ◽  
Ocean Model ◽  
East Antarctica ◽  
Ice Shelf ◽  
Amery Ice Shelf ◽  
Grounding Line ◽  
Lambert Glacier

Abstract. The interaction between the climate system and the large polar ice sheet regions is a key process in global environmental change. We carried out dynamic ice simulations of one of the largest drainage systems in East Antarctica: the Lambert Glacier–Amery Ice Shelf system, with an adaptive mesh ice sheet model. The ice sheet model is driven by surface accumulation and basal melt rates computed by the FESOM (Finite-Element Sea-Ice Ocean Model) ocean model and the RACMO2 (Regional Atmospheric Climate Model) and LMDZ4 (Laboratoire de Météorologie Dynamique Zoom) atmosphere models. The change of ice thickness and velocity in the ice shelf is mainly influenced by the basal melt distribution, but, although the ice shelf thins in most of the simulations, there is little grounding line retreat. We find that the Lambert Glacier grounding line can retreat as much as 40 km if there is sufficient thinning of the ice shelf south of Clemence Massif, but the ocean model does not provide sufficiently high melt rates in that region. Overall, the increased accumulation computed by the atmosphere models outweighs ice stream acceleration so that the net contribution to sea level rise is negative.

scholarly journals Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)

2020 ◽  
Vol 13 (5) ◽  
pp. 2355-2377
Author(s):  
Vijay S. Mahadevan ◽  
Iulian Grindeanu ◽  
Robert Jacob ◽  
Jason Sarich
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
System Modeling ◽  
Spectral Element ◽  
Scientific Workflow ◽  
Model Coupling ◽  
Earth System ◽  
Modeling Framework

Abstract. One of the fundamental factors contributing to the spatiotemporal inaccuracy in climate modeling is the mapping of solution field data between different discretizations and numerical grids used in the coupled component models. The typical climate computational workflow involves evaluation and serialization of the remapping weights during the preprocessing step, which is then consumed by the coupled driver infrastructure during simulation to compute field projections. Tools like Earth System Modeling Framework (ESMF) (Hill et al., 2004) and TempestRemap (Ullrich et al., 2013) offer capability to generate conservative remapping weights, while the Model Coupling Toolkit (MCT) (Larson et al., 2001) that is utilized in many production climate models exposes functionality to make use of the operators to solve the coupled problem. However, such multistep processes present several hurdles in terms of the scientific workflow and impede research productivity. In order to overcome these limitations, we present a fully integrated infrastructure based on the Mesh Oriented datABase (MOAB) (Tautges et al., 2004; Mahadevan et al., 2015) library, which allows for a complete description of the numerical grids and solution data used in each submodel. Through a scalable advancing-front intersection algorithm, the supermesh of the source and target grids are computed, which is then used to assemble the high-order, conservative, and monotonicity-preserving remapping weights between discretization specifications. The Fortran-compatible interfaces in MOAB are utilized to directly link the submodels in the Energy Exascale Earth System Model (E3SM) to enable online remapping strategies in order to simplify the coupled workflow process. We demonstrate the superior computational efficiency of the remapping algorithms in comparison with other state-of-the-science tools and present strong scaling results on large-scale machines for computing remapping weights between the spectral element atmosphere and finite volume discretizations on the polygonal ocean grids.

scholarly journals Dependence of Eemian Greenland temperature reconstructions on the ice sheet topography

2013 ◽  
Vol 9 (6) ◽  
pp. 6683-6732
Author(s):  
N. Merz ◽  
A. Born ◽  
C. C. Raible ◽  
H. Fischer ◽  
T. F. Stocker
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Large Scale ◽  
Surface Energy Balance ◽  
Climate Model ◽  
Surface Wind ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Lapse Rate

Abstract. The influence of a reduced Greenland ice sheet (GrIS) on Greenland's surface climate during the Eemian interglacial is studied using a comprehensive climate model. We find a distinct impact of changes in the GrIS topography on Greenland's surface air temperatures (SAT) even when correcting for changes in surface elevation which influences SAT through the lapse rate effect. The resulting lapse rate corrected SAT anomalies are thermodynamically driven by changes in the local surface energy balance rather than dynamically caused through anomalous advection of warm/cold air masses. The large-scale circulation is indeed very stable among all sensitivity experiments and the NH flow pattern does not depend on Greenland's topography in the Eemian. In contrast, Greenland's surface energy balance is clearly influenced by changes in the GrIS topography and this impact is seasonally diverse. In winter, the variable reacting strongest to changes in the topography is the sensible heat flux (SHFLX). The reason is its dependence on surface winds, which themselves are controlled to a large extent by the shape of the GrIS. Hence, regions where a receding GrIS causes higher surface wind velocities also experience anomalous warming through SHFLX. Vice-versa, regions that become flat and ice-free are characterized by low wind speeds, low SHFLX and anomalous cold winter temperatures. In summer, we find surface warming induced by a decrease in surface albedo in deglaciated areas and regions which experience surface melting. The Eemian temperature records derived from Greenland proxies, thus, likely include a temperature signal arising from changes in the GrIS topography. For the NEEM ice core site, our model suggests that up to 3.2 °C of the annual mean Eemian warming can be attributed to these topography-related processes and hence is not necessarily linked to large-scale climate variations.

Physics, Resolution and Data Assimilation: Making sense of Greenland climate and ice sheet Surface Mass Balance with HARMONIE Climate

2021 ◽  
Author(s):  
Ruth Mottram ◽  
Oskar Landgren ◽  
Rasmus Anker Pedersen ◽  
Kristian Pagh Nielsen ◽  
Ole Bøssing Christensen ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Climate Model ◽  
Weather Prediction ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass ◽  
Mass Budget ◽  
Numerical Weather

<p>The development of the HARMONIE model system has led to huge advances in numerical weather prediction, including over Greenland where a numerical weather prediction (NWP) model is used to forecast daily surface mass budget over the Greenland ice sheet as presented on polarportal.dk. The new high resolution Copernicus Arctic Reanalysis further developed the possibilities in HARMONIE with full 3DVar data assimilation and extended use of quality-controlled local observations. Here, we discuss the development and current status of the climate version of the HARMONIE Climate model (HCLIM). The HCLIM system has opened up the possibility for flexible use of the model at a range of spatial scales using different physical schemes including HARMONIE-AROME, ALADIN and ALARO for different spatial and temporal resolutions and assimilating observations, including satellite data on sea ice concentration from ESA CCI+, to improve hindcasts. However, the range of possibilities means that documenting the effects of different physics and parameterisation schemes is important before widespread application. </p><p>Here, we focus on HCLIM performance over the Greenland ice sheet, using observations to verify the different plausible set-ups and investigate biases in climate model outputs that affect the surface mass budget (SMB) of the Greenland ice sheet. </p><p>The recently funded Horizon 2020 project PolarRES will use the HCLIM model for very high resolution regional downscaling, together with other regional climate models in both Arctic and Antarctic regions, and our analysis thus helps to optimise the use of HCLIM in the polar regions for different modelling purposes.</p>

scholarly journals Statistical downscaling of a climate simulation of the last glacial cycle: temperature and precipitation over Northern Europe

2014 ◽  
Vol 10 (4) ◽  
pp. 1489-1500 ◽  
Author(s):  
N. Korhonen ◽  
A. Venäläinen ◽  
H. Seppä ◽  
H. Järvinen
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Ice Sheet ◽  
Additive Models ◽  
Northern Europe ◽  
Glacial Cycle ◽  
Explanatory Variables ◽  
Last Glacial ◽  
Temperature And Precipitation ◽  
The Last Glacial

Abstract. Earth system models of intermediate complexity (EMICs) have proven to be able to simulate the large-scale features of glacial–interglacial climate evolution. For many climatic applications the spatial resolution of the EMICs' output is, however, too coarse, and downscaling methods are needed. In this study we introduce a way to use generalized additive models (GAMs) for downscaling the large-scale output of an EMIC in very different climatological conditions ranging from glacial periods to current relatively warm climates. GAMs are regression models in which a combination of explanatory variables is related to the response through a sum of spline functions. We calibrated the GAMs using observations of the recent past climate and the results of short time-slice simulations of glacial climate performed by the relatively high-resolution general circulation model CCSM (Community Climate System Model) and the regional climate model RCA3 (Rossby Centre regional Atmospheric climate model). As explanatory variables we used the output of a simulation by the CLIMBER-2 (CLIMate and BiosphERe model 2) EMIC of the last glacial cycle, coupled with the SICOPOLIS (SImulation COde for POLythermal Ice Sheets) ice sheet model, i.e. the large-scale temperature and precipitation data of CLIMBER-2, and the elevation, distance to ice sheet, slope direction and slope angle from SICOPOLIS. The fitted GAMs were able to explain more than 96% of the temperature response with a correlation of >0.98 and more than 59% of the precipitation response with a correlation of >0.72. The first comparison with two pollen-based reconstructions of temperature for Northern Europe showed that CLIMBER-2 data downscaled by GAMs corresponded better with the reconstructions than did the bilinearly interpolated CLIMBER-2 surface temperature.

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

scholarly journals Evaluation of the updated regional climate model RACMO2.3: summer snowfall impact on the Greenland Ice Sheet

2015 ◽  
Vol 9 (5) ◽  
pp. 1831-1844 ◽  
Author(s):  
B. Noël ◽  
W. J. van de Berg ◽  
E. van Meijgaard ◽  
P. Kuipers Munneke ◽  
R. S. W. van de Wal ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Elevation Gradient ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Cores ◽  
Detailed Comparison ◽  
Ablation Zone ◽  
Surface Mass

Abstract. We discuss Greenland Ice Sheet (GrIS) surface mass balance (SMB) differences between the updated polar version of the RACMO climate model (RACMO2.3) and the previous version (RACMO2.1). Among other revisions, the updated model includes an adjusted rainfall-to-snowfall conversion that produces exclusively snowfall under freezing conditions; this especially favours snowfall in summer. Summer snowfall in the ablation zone of the GrIS has a pronounced effect on melt rates, affecting modelled GrIS SMB in two ways. By covering relatively dark ice with highly reflective fresh snow, these summer snowfalls have the potential to locally reduce melt rates in the ablation zone of the GrIS through the snow-albedo-melt feedback. At larger scales, SMB changes are driven by differences in orographic precipitation following a shift in large-scale circulation, in combination with enhanced moisture to precipitation conversion for warm to moderately cold conditions. A detailed comparison of model output with observations from automatic weather stations, ice cores and ablation stakes shows that the model update generally improves the simulated SMB-elevation gradient as well as the representation of the surface energy balance, although significant biases remain.

Global climate simulations at 2.8 km on GPU with the ICON model

2020 ◽  
Author(s):  
Xavier Lapillonne ◽  
William Sawyer ◽  
Philippe Marti ◽  
Valentin Clement ◽  
Remo Dietlicher ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Weather Prediction ◽  
Time Integration ◽  
Horizontal Resolution ◽  
Performance Comparison ◽  
Quasi Biennial Oscillation ◽  
Numerical Weather

<p>The ICON modelling framework is a unified numerical weather and climate model used for applications ranging from operational numerical weather prediction to low and high resolution climate projection. In view of further pushing the frontier of possible applications and to make use of the latest evolution in hardware technologies, parts of the model were recently adapted to run on heterogeneous GPU system. This initial GPU port focus on components required for high-resolution climate application, and allow considering multi-years simulations at 2.8 km on the Piz Daint heterogeneous supercomputer. These simulations are planned as part of the QUIBICC project “The Quasi-Biennial Oscillation (QBO) in a changing climate”, which propose to investigate effects of climate change on the dynamics of the QBO.</p><p>Because of the low compute intensity of atmospheric model the cost of data transfer between CPU and GPU at every step of the time integration would be prohibitive if only some components would be ported to the accelerator. We therefore present a full port strategy where all components required for the simulations are running on the GPU. For the dynamics, most of the physical parameterizations and infrastructure code the OpenACC compiler directives are used. For the soil parameterization, a Fortran based domain specific language (DSL) the CLAW-DSL has been considered. We discuss the challenges associated to port a large community code, about 1 million lines of code, as well as to run simulations on large-scale system at 2.8 km horizontal resolution in terms of run time and I/O constraints. We show performance comparison of the full model on CPU and GPU, achieving a speed up factor of approximately 5x, as well as scaling results on up to 2000 GPU nodes. Finally we discuss challenges and planned development regarding performance portability and high level DSL which will be used with the ICON model in the near future.</p>

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